In this paper, real-time data collection and transmission technologies in the industrial Internet of Things environment are studied. Through strategies such as adaptive sampling, event-driven sampling, MQTT and CoAP protocol optimization, data compression and encryption, the system performance is significantly improved. Experimental results show that these optimization strategies effectively reduce data collection frequency and transmission delay, reduce bandwidth occupation, reduce data packet loss rate, and improve data processing efficiency. Among them, data compression and encryption technologies improve transmission performance while maintaining data security, providing practical optimization solutions for data transmission in industrial Internet of Things, and have certain application value.